Add autodiff
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Draft for minimal integration of automatic differentiation. Tensorflow and Torch backend were removed (apart from AutoDiffOp.create_tensorlfow())
Only tests without LBM or tf/torch dependencies have been added. This implies that also numeric gradient checking is missing (depends on either tf or torch). Should we really move the backends into separate modules?
Apart from adding auto-differentiation functionality I added two more changes. Would be happy to AutoDiffOp.create_tensorflow() after feedback.
Edited by Martin Bauer
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265 270 elif isinstance(cpu_vectorize_info, dict): 266 271 vectorize(ast, **cpu_vectorize_info) 267 272 return ast 273 274 275 def make_python_function(kernel_function_node, target='cpu', argument_dict=None): -
Probably not necessary, since the suitable "make_python_function" is available as ast.compile()
Edited by Martin Bauer
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